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A Robust Variable Forgetting Factor Recursive Least-Squares Algorithm for System Identification

机译:用于系统辨识的鲁棒变量遗忘因子递推最小二乘算法

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摘要

The performance of the recursive least-squares (RLS) algorithm is governed by the forgetting factor. This parameter leads to a compromise between (1) the tracking capabilities and (2) the misadjustment and stability. In this letter, a variable forgetting factor RLS (VFF-RLS) algorithm is proposed for system identification. In general, the output of the unknown system is corrupted by a noise-like signal. This signal should be recovered in the error signal of the adaptive filter after this one converges to the true solution. This condition is used to control the value of the forgetting factor. The simulation results indicate the good performance and the robustness of the proposed algorithm.
机译:递归最小二乘(RLS)算法的性能由遗忘因子决定。此参数导致(1)跟踪功能与(2)失调与稳定性之间的折衷。在这封信中,提出了一种变量遗忘因子RLS(VFF-RLS)算法用于系统识别。通常,未知系统的输出会被类似噪声的信号破坏。该信号收敛到真实解后,应在自适应滤波器的误差信号中恢复该信号。此条件用于控制遗忘因子的值。仿真结果表明了该算法的良好性能和鲁棒性。

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